agricolaeplotr (version 0.6.1)

plot_split_crd: Plot Split Plot Designs (crd)

Description

Plot a design of a split plot experiment with a complete randomized design (crd) from design.split

Usage

plot_split_crd(
  design,
  nrows,
  ncols,
  factor_name_1 = "T1",
  factor_name_2 = "T2",
  labels = "plots",
  subplots = TRUE,
  width = 1,
  height = 1,
  space_width = 0.95,
  space_height = 0.85,
  reverse_y = FALSE,
  reverse_x = FALSE
)

Value

ggplot graphic that can be modified, if wished

Arguments

design

outdesign from agricolae package

nrows

Number of rows for the design

ncols

Number of columns for the design

factor_name_1

string Which factor should be used for plotting, needs to be a column in outdesign$book

factor_name_2

string Which factor should be used for plotting, needs to be a column in outdesign$book

labels

string Describes the column from that the plots are taken to display them

subplots

should the plot function return the subplots (default) or main plots?

width

numeric value, describes the width of a plot in an experiment

height

numeric value, describes the height of a plot in an experiment

space_width

numeric value, describes the share of the space of the plots. 0=only space, 1=no space between plots in term of width

space_height

numeric value, describes the share of the space of the plots. 0=only space, 1=no space between plots in term of height

reverse_y

boolean, should the plots of the experiment be changed in reverse order in Row direction? use reverse_y=TRUE to have same sketch as in agricolae. default:reverse_y=FALSE

reverse_x

boolean, should the plots of the experiment be changed in reverse order in column direction? default:reverse_x=FALSE

Examples

library(agricolaeplotr)
library(agricolae)
T1<-c('a','b','c','d','e','f','g')
T2<-c('v','w','x','y','zzz')
r <- 4
outdesign2 <- design.split(trt1=T1, trt2=T2, r=r,
serie = 2, seed = 0, kinds = 'Super-Duper',
randomization=TRUE,first=TRUE,design = 'crd')
plot_split_crd(outdesign2,ncols = 6,nrows=5)

outdesign2 <- design.split(trt1=T1, trt2=T2, r=r,
serie = 2, seed = 0, kinds = 'Super-Duper',
randomization=FALSE,first=TRUE,design = 'crd')
plot_split_crd(outdesign2,ncols = 6,nrows=5)